fgem_bfgs: fit fgem using lbfgs

In CreRecombinase/FGEM: R package for Functional Genomics using Expectation Maximization (FGEM)

Description

fit fgem using lbfgs

Usage

fgem_bfgs(
  X,
  BF,
  Beta0 = c(0, rep(0, ncol(X))),
  verbose = FALSE,
  alpha = 1,
  lambda = c(2, 1, 5 * 10^(-(seq(1, 6, length.out = 75))), 0),
  add_lambda = FALSE,
  progress = FALSE,
  log_BF = FALSE,
  ...
)

Arguments

X	feature matrix
BF	vector of bayes factors
Beta0	initial guess (defaults to 0)
verbose	(whether to give verbose output)
alpha	alpha (as in glmnet). Alpha is the (scalar) proportion of 'lambda' applied to l1 penalization, while '1-alpha' is applied to l2
lambda	vector of shrinkage parameters
...	currently unused

Value

tibble with results of fit

CreRecombinase/FGEM documentation built on July 17, 2020, 5:30 a.m.